Skip to content
2000
Volume 11, Issue 1
  • ISSN: 2667-3371
  • E-ISSN: 2667-338X

Abstract

While extending treatment protocols and refining systematic processes within the healthcare industry presents immense promise, artificial intelligence (AI) comes along with multiple benefits. It would arrive at accurate diagnoses of diseases, help generate personalized treatment plans, facilitate corporate interactions in healthcare systems, and benefit both patients and healthcare organizations. With the evolving trends in AI, the healthcare domain expects to see substantial effects in the coming few years, hence calling for strong regulation to ensure the protection of human ethics and practical application. The establishment of common regulatory frameworks will enable responsible usages of AI while accentuating patient rights and privacy concerns. AI is changing how drug approvals are done through positive interventions on both the time and cost aspects.

Whereas traditional drug development takes anywhere from 5.5 years to 14.5 years, AI has shortened this time frame for target discovery to a preclinical candidate to as little as 18 months. Furthermore, AI has reduced development costs by nearly 50%, thus rendering development more efficient while enhancing the accuracy of predictions of the efficacy and safety of drugs. The stepped integration of AI into drug approval processes accelerates innovations by providing cost-effective solutions and enhancing precision that eventually benefits both patients and healthcare organizations.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/adctra/10.2174/0126673371376328250602101734
2025-06-18
2025-12-09

  • From This Site

    /content/journals/adctra/10.2174/0126673371376328250602101734
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. RivareA. Artificial intelligence and digitalization in pharmaceutical regulatory affairs.Dissertation, University of Helsinki2023
     [Google Scholar]
  2. ShelarS. BagdaneS. JoshiP. Drug regulatory affairs: The potential for machine learning and Artificial Intelligence.Pharm. Reson202462110
     [Google Scholar]
  3. FrölingE. RajaeeanN. HinrichsmeyerK.S. Domrös-ZoungranaD. UrbanJ.N. LenzC. Artificial Intelligence in medical affairs: A new paradigm with novel opportunities.Pharmaceut. Med.202438533134210.1007/s40290‑024‑00536‑939259426
     [Google Scholar]
  4. HanY. TaoJ. Revolutionizing pharma: Unveiling the AI and LLM trends in the pharmaceutical industry.arXiv:2401102732024
     [Google Scholar]
  5. KapustinaO. User-friendly and industry-integrated AI for medicinal chemists and pharmaceuticals.Artif Intell Chem2024100072
     [Google Scholar]
  6. ViswaCA Generative AI in the pharmaceutical industry: Moving from hype to reality.2024
     [Google Scholar]
  7. UllagaddiP. Leveraging digital transformation for enhanced risk mitigation and compliance in pharma manufacturing.J. Adv. Med. Pharm. Sci.2024266758610.9734/jamps/2024/v26i6697
     [Google Scholar]
  8. SampeneA.K. NyirendaF. Evaluating the effect of Artificial Intelligence on pharmaceutical product and drug discovery in China.Future J. Pharm. Sci.20241015810.1186/s43094‑024‑00632‑2
     [Google Scholar]
  9. ChallaS.S.S. Streamlining change control processes in regulatory affairs: Best practices and case studies.Integr J Res Arts Humanit202444677510.55544/ijrah.4.4.12
     [Google Scholar]
  10. HigginsD. MadaiV.I. From bit to bedside: A practical framework for artificial intelligence product development in healthcare.Adv. Intell. Syst.2020210200005210.1002/aisy.202000052
     [Google Scholar]
  11. AlowaisS.A. AlghamdiS.S. AlsuhebanyN. Revolutionizing healthcare: The role of artificial intelligence in clinical practice.BMC Med. Educ.202323168910.1186/s12909‑023‑04698‑z37740191
     [Google Scholar]
  12. VenkatesanK. A textbook on Artificial Intelligence in precision medicine, drug development, and healthcare.
     [Google Scholar]
  13. UllagaddiP. Digital transformation strategies to strengthen quality and data integrity in pharma.Int. J. Bus. Manage.2024195162610.5539/ijbm.v19n5p16
     [Google Scholar]
  14. PrabhodK.J. Leveraging generative AI for personalized medicine: Applications in drug discovery and development.J AI-Assist Sci Discov202331392434
     [Google Scholar]
  15. SmuhaN.A. From a ‘race to AI’ to a ‘race to AI regulation’: Regulatory competition for artificial intelligence.Law Innov. Technol.2021131578410.1080/17579961.2021.1898300
     [Google Scholar]
  16. NcubeB.M. DubeA. WardK. Establishment of the African Medicines Agency: Progress, challenges and regulatory readiness.J. Pharm. Policy Pract.20211412910.1186/s40545‑020‑00281‑933685518
     [Google Scholar]
  17. TerryN. Appification, AI, and healthcare’s new iron triangle.SSRN20172011710.2139/ssrn.3020784
     [Google Scholar]
  18. ChoudhuryA. AsanO. Role of artificial intelligence in patient safety outcomes: Systematic literature review.JMIR Med. Inform.202087e1859910.2196/1859932706688
     [Google Scholar]
  19. Chanfreau-CoffinierC. HullL.E. LynchJ.A. Projected prevalence of actionable pharmacogenetic variants and level A drugs prescribed among US Veterans Health Administration pharmacy users.JAMA Netw. Open201926e195345e510.1001/jamanetworkopen.2019.534531173123
     [Google Scholar]
  20. O’ConnorT.F. YuL.X. LeeS.L. Emerging technology: A key enabler for modernizing pharmaceutical manufacturing and advancing product quality.Int. J. Pharm.20165091-249249810.1016/j.ijpharm.2016.05.05827260134
     [Google Scholar]
  21. GoldbergC.B. To do no harm—and the most good—with AI in health care.Nat. Med.20243062362710.1038/s41591‑024‑02853‑7
     [Google Scholar]
  22. SolomonD.H. RudinR.S. Digital health technologies: Opportunities and challenges in rheumatology.Nat. Rev. Rheumatol.202016952553510.1038/s41584‑020‑0461‑x32709998
     [Google Scholar]
  23. SchererM.U. Regulating artificial intelligence systems: Risks, challenges, competencies, and strategies.SSRN20152935310.2139/ssrn.2609777
     [Google Scholar]
  24. NaikN. HameedB.M.Z. ShettyD.K. Legal and ethical consideration in artificial intelligence in healthcare: Who takes responsibility?Front. Surg.2022986232210.3389/fsurg.2022.86232235360424
     [Google Scholar]
  25. FriedmanM.A. WoodcockJ. LumpkinM.M. ShurenJ.E. HassA.E. ThompsonL.J. The safety of newly approved medicines: Do recent market removals mean there is a problem?JAMA1999281181728173410.1001/jama.281.18.172810328074
     [Google Scholar]
  26. QuaziS. Artificial intelligence and machine learning in precision and genomic medicine.Med. Oncol.202239812010.1007/s12032‑022‑01711‑135704152
     [Google Scholar]
  27. GrimsrudK.N. SherwinC.M.T. ConstanceJ.E. Special population considerations and regulatory affairs for clinical research.Clin. Res. Regul. Aff.2015322455410.3109/10601333.2015.100190026401094
     [Google Scholar]
  28. EngstromD.F. Government by algorithm: Artificial intelligence in federal administrative agencies.NYU School of Law, Public Law Research Paper2020455410.2139/ssrn.3551505
     [Google Scholar]
  29. LanthierM. MillerK.L. NardinelliC. WoodcockJ. An improved approach to measuring drug innovation finds steady rates of first-in-class pharmaceuticals, 1987-2011.Health Aff.20133281433143910.1377/hlthaff.2012.054123918488
     [Google Scholar]
  30. PittsP.J. LouetH.L. MorideY. ContiR.M. 21st century pharmacovigilance: Efforts, roles, and responsibilities.Lancet Oncol.20161711e486e49210.1016/S1470‑2045(16)30312‑627819246
     [Google Scholar]
  31. MinssenT. Governing AI in the European Union: Emerging infrastructures and regulatory ecosystems in health.Research Handbook on Health, AI and the Law.Cheltenham, UKEdward Elgar Publishing Ltd202410.4337/9781802205657.00027
     [Google Scholar]
  32. SafaviK. MathewsS.C. BatesD.W. DorseyE.R. CohenA.B. Top-funded digital health companies and their impact on high-burden, high-cost conditions.Health Aff.201938111512310.1377/hlthaff.2018.0508130615535
     [Google Scholar]
  33. SternA.D. Innovation under regulatory uncertainty: Evidence from medical technology.J. Public Econ.201714518120010.1016/j.jpubeco.2016.11.01028652646
     [Google Scholar]
  34. TrubyJ. BrownR. DahdalA. Banking on AI: Mandating a proactive approach to AI regulation in the financial sector.Law and Financial Markets Review202014211012010.1080/17521440.2020.1760454
     [Google Scholar]
  35. SchuettJ. From principles to rules: A regulatory approach for frontier AI.arXiv:2407073002024
     [Google Scholar]
  36. FeijóoC. KwonY. BauerJ.M. Harnessing artificial intelligence (AI) to increase wellbeing for all: The case for a new technology diplomacy.Telecomm. Policy202044610198810.1016/j.telpol.2020.10198832377031
     [Google Scholar]
  37. AbernethyA. The promise of digital health: Then, now, and the future.NAM Perspect.202210.31478/202206e10.31478/202206e
     [Google Scholar]
  38. HazarikaI. Artificial intelligence: Opportunities and implications for the health workforce.Int. Health202012424124510.1093/inthealth/ihaa00732300794
     [Google Scholar]
  39. BergerM.L. LipsetC. GutteridgeA. AxelsenK. SubediP. MadiganD. Optimizing the leveraging of real-world data to improve the development and use of medicines.Value Health201518112713010.1016/j.jval.2014.10.00925595243
     [Google Scholar]
  40. XuJ. YangP. XueS. Translating cancer genomics into precision medicine with artificial intelligence: Applications, challenges and future perspectives.Hum. Genet.2019138210912410.1007/s00439‑019‑01970‑530671672
     [Google Scholar]
  41. Zobel-RoosS. SchmidtA. MestmäckerF. Accelerating biologics manufacturing by modeling or: Is approval under the QbD and PAT approaches demanded by authorities acceptable without a digital-twin?Processes2019729410.3390/pr7020094
     [Google Scholar]
  42. StahlB.C. Artificial intelligence for a better future: an ecosystem perspective on the ethics of AI and emerging digital technologies.Springer Nature202110.1007/978‑3‑030‑69978‑9
     [Google Scholar]
  43. LobelO. The law of AI for good.Fla. Law Rev.202375107310.2139/ssrn.4338862
     [Google Scholar]
  44. PanayidesA.S. AminiA. FilipovicN.D. AI in medical imaging informatics: Current challenges and future directions.IEEE J. Biomed. Health Inform.20202471837185710.1109/JBHI.2020.299104332609615
     [Google Scholar]
  45. RockW.R.L. Artificial Intelligence (AI) in Arkansas.(AR)Preprint2020
     [Google Scholar]
  46. LalitV. Operational challenges in modern business evolution in healthcare technology startups.Healthcare Industry Assessment: Analyzing Risks, Security, and Reliability Engineering Cyber-Physical Systems and Critical Infrastructures.ChamSpringer20241110.1007/978‑3‑031‑65434‑3_13
     [Google Scholar]
  47. CohenI.G. Informed consent and medical artificial intelligence: What to tell the patient?Geol. J.2019108142510.2139/ssrn.3529576
     [Google Scholar]
  48. BandyopadhyayA. OksM. SunH. Strengths, weaknesses, opportunities, and threats of using AI-enabled technology in sleep medicine: A commentary.J. Clin. Sleep Med.20242071183119110.5664/jcsm.1113238533757
     [Google Scholar]
  49. PovsicT.J. KorjianS. BahitM.C. Effect of reconstituted human apolipoprotein AI on recurrent ischemic events in survivors of acute MI.J. Am. Coll. Cardiol.202483222163217410.1016/j.jacc.2024.03.39638588930
     [Google Scholar]
  50. HolderC. KhuranaV. HarrisonF. JacobsL. Robotics and law: Key legal and regulatory implications of the robotics age (Part I of II).Comput. Law Secur. Rev.201632338340210.1016/j.clsr.2016.03.001
     [Google Scholar]
  51. LuepkeK.H. MohrJ.F. The antibiotic pipeline: Reviving research and development and speeding drugs to market.Expert Rev. Anti Infect. Ther.201715542543310.1080/14787210.2017.130825128306360
     [Google Scholar]
  52. RasoFA Berkman Klein Center Research Publication20182018-6
     [Google Scholar]
  53. FountzilasE. TsimberidouA.M. VoH.H. KurzrockR. Clinical trial design in the era of precision medicine.Genome Med.202214110110.1186/s13073‑022‑01102‑136045401
     [Google Scholar]
  54. HeJ. BaxterS.L. XuJ. XuJ. ZhouX. ZhangK. The practical implementation of artificial intelligence technologies in medicine.Nat. Med.2019251303610.1038/s41591‑018‑0307‑030617336
     [Google Scholar]
  55. WieselerB. McGauranN. KaiserT. New drugs: Where did we go wrong and what can we do better?BMJ2019366l434010.1136/bmj.l434031292109
     [Google Scholar]
  56. DumonteilE. BottazziM.E. ZhanB. Accelerating the development of a therapeutic vaccine for human Chagas disease: Rationale and prospects.Expert Rev. Vaccines20121191043105510.1586/erv.12.8523151163
     [Google Scholar]
  57. FregniF. NitscheM.A. LooC.K. Regulatory considerations for the clinical and research use of transcranial direct current stimulation (tDCS): Review and recommendations from an expert panel.Clin. Res. Regul. Aff.2015321223510.3109/10601333.2015.98094425983531
     [Google Scholar]
  58. ChaudhariY. Computational pharmaceutics: A comprehensive review of past achievements, present applications, and future challenges.Preprint2024
     [Google Scholar]
  59. BiswasI. SinghR. Application of AI and blockchain in healthcare industry–A review.J Adv Zool2024452
     [Google Scholar]
  60. VazM. SilvaV. MonteiroC. SilvestreS. Role of aducanumab in the treatment of Alzheimer’s disease: Challenges and opportunities.Clin. Interv. Aging20221779781010.2147/CIA.S32502635611326
     [Google Scholar]
  61. GongB. NugentJ.P. GuestW. Influence of artificial intelligence on Canadian medical students’ preference for radiology specialty: A national survey study.Acad. Radiol.201926456657710.1016/j.acra.2018.10.00730424998
     [Google Scholar]
  62. MitsalaA. TsalikidisC. PitiakoudisM. SimopoulosC. TsarouchaA.K. Artificial intelligence in colorectal cancer screening, diagnosis and treatment. A new era.Curr. Oncol.20212831581160710.3390/curroncol2803014933922402
     [Google Scholar]
  63. CramerJ.A. MintzerS. WhelessJ. MattsonR.H. Adverse effects of antiepileptic drugs: A brief overview of important issues.Expert Rev. Neurother.201010688589110.1586/ern.10.7120518605
     [Google Scholar]
  64. BenbyaH. DavenportT.H. PachidiS. Artificial intelligence in organizations: Current state and future opportunities.MIS Q. Exec.202019410.2139/ssrn.3741983
     [Google Scholar]
  65. LadensonP.W. KristensenJ.D. RidgwayE.C. Use of the thyroid hormone analogue eprotirome in statin-treated dyslipidemia.N. Engl. J. Med.20103621090691610.1056/NEJMoa090563320220185
     [Google Scholar]
  66. LanjouwJ. Patents, price controls, and access to new drugs: How policy affects global market entry.Mass., USANational Bureau of Economic Research Cambridge2005
     [Google Scholar]
  67. JinF.Y. KamannaV.S. KashyapM.L. Niacin accelerates intracellular ApoB degradation by inhibiting triacylglycerol synthesis in human hepatoblastoma (HepG2) cells.Arterioscler. Thromb. Vasc. Biol.19991941051105910.1161/01.ATV.19.4.105110195935
     [Google Scholar]
  68. GrahamS.A. LeeE.E. JesteD.V. Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.Psychiatry Res.202028411273210.1016/j.psychres.2019.11273231978628
     [Google Scholar]
  69. JobinA. IencaM. VayenaE. The global landscape of AI ethics guidelines.Nat. Mach. Intell.20191938939910.1038/s42256‑019‑0088‑2
     [Google Scholar]
  70. VigneshM. AI-Powered Advances in Pharmacology.Springer Nature202461
     [Google Scholar]
  71. MatthewsB.R. Regulatory aspects of stability testing in Europe.Drug Dev. Ind. Pharm.199925783185610.1081/DDC‑10010224510459489
     [Google Scholar]
  72. IgbinosaE.O. OkohA.I. Impact of discharge wastewater effluents on the physico-chemical qualities of a receiving watershed in a typical rural community.Int. J. Environ. Sci. Technol.20096217518210.1007/BF03327619
     [Google Scholar]
  73. CaloR. Artificial intelligence policy: A primer and roadmap.UCD Law Rev.20175139910.2139/ssrn.3015350
     [Google Scholar]
  74. HamM. MossA.C. Mesalamine in the treatment and maintenance of remission of ulcerative colitis.Expert Rev. Clin. Pharmacol.20125211312310.1586/ecp.12.222390554
     [Google Scholar]
  75. ÖzdemirV. HekimN. Birth of industry 5.0: Making sense of big data with artificial intelligence,“the internet of things” and next-generation technology policy.OMICS2018221657610.1089/omi.2017.019429293405
     [Google Scholar]
  76. FurmanJ. SeamansR. AI and the Economy.Innov. Policy Econ.201919116119110.1086/699936
     [Google Scholar]
  77. KaandersJ.H.A.M. PopL.A.M. MarresH.A.M. Accelerated radiotherapy with carbogen and nicotinamide (ARCON) for laryngeal cancer.Radiother. Oncol.199848211512210.1016/S0167‑8140(98)00043‑79783882
     [Google Scholar]
  78. ReisJ. SantoP.E. MelãoN. Impacts of artificial intelligence on public administration: A systematic literature review.14th Iberian Conference on Information Systems and Technologies (CISTI)Coimbra, Portugal19-22 June20191710.23919/CISTI.2019.8760893
     [Google Scholar]
  79. JohnsonD.K. WilkinsC.H. MorrisJ.C. Accelerated weight loss may precede diagnosis in Alzheimer disease.Arch. Neurol.20066391312131710.1001/archneur.63.9.131216966511
     [Google Scholar]
/content/journals/adctra/10.2174/0126673371376328250602101734
Loading
Advancing Regulatory Framework with AI: A Step Towards Quicker Medication
Appl. Drug Resea., Clin. Trials and Regu. Affa. 11, E26673371376328 (2025); https://doi.org/10.2174/0126673371376328250602101734
/content/journals/adctra/10.2174/0126673371376328250602101734
/content/journals/adctra/10.2174/0126673371376328250602101734
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): accelerated approvals; advancements of AI in regulatory affairs; Artificial intelligence; cost-effective solutions; drug development; healthcare systems; medicine

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test